U.S. patent application number 10/855634 was filed with the patent office on 2004-11-25 for real-time aggregation of data within an enterprise planning environment.
This patent application is currently assigned to Adaytum, Inc.. Invention is credited to Gould, Michael, Pearson, George Duncan, Sandles, Jon M., Thier, Adam.
Application Number | 20040236738 10/855634 |
Document ID | / |
Family ID | 32030255 |
Filed Date | 2004-11-25 |
United States Patent
Application |
20040236738 |
Kind Code |
A1 |
Thier, Adam ; et
al. |
November 25, 2004 |
Real-time aggregation of data within an enterprise planning
environment
Abstract
An enterprise business planning system includes a database
having a relational data area and a transactional data area, and a
server to store within the transactional data area contribution
data received from a set of enterprise contributors. The server
publishes the contribution data from the transactional data area to
the relational data area. The transactional data area may include a
set of contribution slots and a set of aggregations slots
hierarchically related in accordance with an enterprise model. The
relational area includes a set of related tables defined in
accordance with the model. The transactional data area supports
real-time interaction with the enterprise contributors, while the
relational data area allows detailed statistical analysis and
report generation.
Inventors: |
Thier, Adam; (Burnsville,
MN) ; Sandles, Jon M.; (York, GB) ; Pearson,
George Duncan; (Firby, GB) ; Gould, Michael;
(Easingwold, GB) |
Correspondence
Address: |
SHUMAKER & SIEFFERT, P. A.
8425 SEASONS PARKWAY
SUITE 105
ST. PAUL
MN
55125
US
|
Assignee: |
Adaytum, Inc.
|
Family ID: |
32030255 |
Appl. No.: |
10/855634 |
Filed: |
May 27, 2004 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10855634 |
May 27, 2004 |
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10262591 |
Sep 30, 2002 |
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6768995 |
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Current U.S.
Class: |
1/1 ;
707/999.004 |
Current CPC
Class: |
Y10S 707/99945 20130101;
G06F 16/24556 20190101 |
Class at
Publication: |
707/004 |
International
Class: |
G06F 007/00 |
Claims
1. A system comprising: a database having a relational data area
and a transactional data area; and a server to store within the
transactional data area contribution data received from a set of
enterprise contributors, and to publish the contribution data from
the transactional data area to the relational data area.
2. The system of claim 1, wherein the transactional data area
includes a set of contribution slots to store the contribution data
and aggregations slots to store aggregated totals of the
contribution data, wherein the contribution slots and aggregation
slots are hierarchically related in accordance with an enterprise
model.
3. The system of claim 2, wherein the transactional data area
includes a respective one of the contribution slot for each of the
enterprise contributors to store the contribution data received
from the respective enterprise contributors.
4. The system of claim 3, wherein the enterprise model has
hierarchically arranged nodes, each node associated with at least
one network user, and the transaction data area includes a slot for
each of the nodes of the enterprise model.
5. The system of claim 4, wherein the hierarchically arranged nodes
comprise N nodes associated with the enterprise contributors, and M
nodes associated with a set of enterprise reviewers, and the
transactional data area comprises N+M slots.
6. The system of claim 3, wherein for each enterprise contributor
the server: receives the contribution data from the enterprise
contributor; selects in accordance with the enterprise model a
respective slot from the set of contribution slots; and stores the
contribution data received from the enterprise contributor within
the selected slot.
7. The system of claim 2, wherein the database stores the
contribution data and the aggregation totals in a format compliant
with a data description language.
8. The system of claim 2, wherein in response to an access request
from one of the reviewers, the server selects the aggregation slot
associated with the reviewer by the enterprise model, and presents
for review the aggregation totals from the selected aggregation
slot and the contribution data stored by a set of the contribution
slots related to the selected aggregation slots in accordance with
the enterprise model.
9 The system of claim 2, wherein the server receives review
information from the reviewer that accepts or rejects the
contribution data stored within contribution slots related to the
selected aggregation slots by the enterprise model, and selectively
updates the selected aggregation slot in response to the review
information.
10. The system of claim 2, wherein the server: receives the
contribution data from the enterprise contributors; selects
contribution slots associated with the enterprise contributors in
accordance with the enterprise model; updates the selected
contribution slots to stores the received contribution data;
identifies in accordance with the enterprise model any of the
aggregation slots related to the updated contribution slots; and
updates the aggregation totals of the identified aggregation slots
based on the received contribution data.
11. The system of claim 1, wherein the relational area comprises a
set of related tables defined in accordance with the enterprise
model, and the server parses the contribution data of the
transactional data area to identify a set of data elements, selects
one or more of data tables within the relational data area in
accordance with the enterprise model, and writes the set of data
elements to the selected tables.
12. A system providing a computing environment for enterprise
business planning, the system comprising: a database having a
transactional data area and a relational data area; a set of
servers to present a network interface for real-time review and
aggregation of contribution data within the transactional data area
of the database, and to publish the contribution data to the
relational data area; and a set of analytical software modules
executing within the computing environment to generate business
planning reports based on the contribution data stored within the
relational data area of the database.
13. The system of claim 12, wherein the servers capture the
contribution data from a set of enterprise contributors, and
wherein the transactional data area includes a transaction slot for
each of the enterprise contributors to store the contribution data
received from the respective enterprise contributors.
14. The system of claim 12, wherein the transactional data area
includes a set of contribution slots and a set of aggregation slots
hierarchically related in accordance with an enterprise model.
15 A method comprising: receiving contribution data from an
enterprise contributor of an enterprise in accordance with a
multi-level enterprise model; storing the contribution data for the
enterprise contributor within a transactional area of a database;
publishing the contribution data from the transactional area to a
relational area of the database; and generating a report from the
contribution data of the relational area of the database.
16. The method of claim 15, wherein storing the contribution data
comprises selecting a slot from a set of contribution slots within
the transactional area in accordance with the enterprise model; and
storing the contribution data to the selected slot.
17. The method of claim 15, wherein the transactional data area
includes a set of contribution slots and aggregations slots
hierarchically related in accordance with an enterprise model.
18. The method of claim 17, further comprising: defining the
enterprise model to include N hierarchically arranged nodes; and
associating each node with a enterprise user; and updating each
node to assign the associated enterprise user as one of a
contributor and a reviewer.
19. The method of claim 18, further comprising: calculating
aggregation totals based on the received contribution data; and
updating the aggregation slots to store the calculated aggregation
totals.
20. The method of claim 18, further comprising storing the
contribution data and the aggregation totals in a format compliant
with a data description language.
21. The method of claim 15, further comprising: receiving an access
request from one of a set of enterprise reviewers; selecting, in
response to an access request and in accordance with the enterprise
model, an aggregation slot associated with the reviewer;
identifying contribution slots related to the selected aggregation
slots in accordance with the enterprise model; and presenting for
review the aggregation totals of the selected aggregation slot and
the contribution data stored by the identified contribution
slots.
22. The method of claim 21, further comprising: receiving review
information from the enterprise reviewer that accepts or rejects
the contribution data stored within the identified contribution
slots; and selectively updating the selected aggregation slot in
response to the review information.
23. The method of claim 15, wherein storing the contribution data
comprises storing the contribution data for each contributor and
the aggregation totals for each reviewer in a format compliant with
a data description language.
24 The method of claim 15, wherein the relational area comprises a
set of related tables defined in accordance with the enterprise
model, and publishing the contribution data comprises: parsing the
contribution data of the transactional data to identify a set of
data elements; selecting one or more of data tables within the
relational data area in accordance with the enterprise model; and
writing the set of data elements to the selected tables.
Description
[0001] This application is a continuation of and claims priority to
Ser. No. 10/262,591, filed Sep. 30, 2002, the entire content of
which is incorporated herein by reference.
TECHNICAL FIELD
[0002] The invention relates to enterprise computing environments,
and more particularly, to computing environments for enterprise
business planning.
BACKGROUND
[0003] More than ever before, enterprises are charged with
establishing accurate forecasts for enterprise operations. Failing
to meet established expectations can have significant negative
impact on the enterprise in the areas of cash flow, stock price,
liquidity, and investor faith, among other areas. Examples of
enterprise planning activities for which accuracy is critical
include revenue forecasting, inventory management, resource
planning, and the like. Enterprise business planning, however, is a
difficult and expensive task that often produces inaccurate
results.
[0004] Conventionally, businesses have taken either a "top-down" or
a "bottom-up" approach to enterprise planning. In "top-down"
planning, businesses identify fundamental business targets, such as
average product price, cost per employee, and the like, and push
the targets down through the hierarchical structure of the
corporation. In contrast, "bottom-up" planning involves the
aggregation of low-level forecasts from the lowest cost centers of
an organization. For budget planning, for example, management
personnel may be required to periodically forecast expenses, and
allocate the expenses to a number of categories, such as
advertisement, travel, and salaries. However, the bottom-up
forecasts rarely, if ever, reconcile with top-down business
targets.
[0005] This information has typically been collected using paper
or, more recently, electronic forms, such as an electronic template
created with a spreadsheet software program. This often leaves the
financial department of the enterprise with the difficult task of
consolidating uncoordinated plans that have been compiled using
inconsistent assumptions and varying business logic.
[0006] More recently, large computer systems have been used to
collect the data via an enterprise network. The computer systems
typically consolidate data collected from the various enterprise
users using time-consuming, offline batch processing during "off"
hours. This offline consolidation can lead to significant time
delays between the collection of the data from a user, and the
consolidation of the collected data with other data collected from
the enterprise. As a result, such systems often present users an
inaccurate view of the actual, aggregated data for the enterprise
activity being forecasted. This may lead the users to provide
incorrect data, or erroneously modify their input. Furthermore, the
users may be unsure as to which numbers are the "right" numbers for
the enterprise, and may generally doubt the integrity of the
results. This slow process of data collection and offline
consolidation can be particularly problematic for a heavily
deadline-oriented activity like enterprise planning.
SUMMARY
[0007] The invention is directed to enterprise planning techniques
that improve the accuracy and predictability of budget planning
within large organizations by enabling organizations to reconcile
corporate financial models and organizational targets with detailed
forecasts in real-time. In particular, the techniques make use of
an enterprise planning database system having a transactional data
area for real-time interaction with enterprise users, and a
relational data area for detailed statistical analysis and report
generation.
[0008] According to the techniques, an enterprise planning system
enables and automates the reconciliation of top-down targets with
detailed bottom-up forecasts for an enterprise. Generally, the
enterprise planning system provides three stages of enterprise
planning: (1) a modeling stage, (2) a contribution stage, and (3) a
reconciliation stage. During the modeling stage, high-level
enterprise managers or executives, referred to as analysts, define
organizational targets, and build planning models for the
enterprise. Next, during the contribution phase, a set of defined
contributors interacts with the enterprise planning system and
provides detailed forecasts in the form of contribution data.
During the reconciliation phase, the enterprise planning system
automates the reconciliation of the forecast data with the
organizational targets.
[0009] During this process, the enterprise planning system operates
in accordance with the defined model to provide a hierarchical
planning process having multiple reconciliation levels. At each
level, the enterprise planning system presents the contribution
data to enterprise reviewers, as defined by the hierarchical model,
and requires that the reviewer reconcile the target data with the
forecast data. Each reviewer may, for example, reject or accept the
contribution data in view of corporate targets provided by the
analysts.
[0010] As the contributors provide the contribution data, the
enterprise planning system automatically aggregates the
contribution data across the enterprise in real-time, and presents
the aggregated data to reviewers for acceptance or rejection. This
process continues until the contribution data is ultimately
approved by the reviewers associated with the highest level of the
organizational hierarchy, thereby ensuring that the contribution
data from the contributors reconciles with corporate targets.
[0011] In one embodiment, a system comprises a database having a
relational data area and a transactional data area, and a server to
store within the transactional data area contribution data received
from a set of enterprise contributors, and to publish the
contribution data from the transactional data area to the
relational data area. The transactional data area may include a set
of contribution slots and aggregations slots hierarchically related
in accordance with an enterprise model. The relational area may
comprise a set of related tables defined in accordance with the
model.
[0012] In another embodiment, a method comprises receiving
contribution data from a contributor of an enterprise in accordance
with a multi-level enterprise model, and storing the contribution
data for the contributor within a transactional area of a database.
The method further comprises publishing the contribution data from
the transactional area to a relational area of the database, and
generating a report from the contribution data of the relational
area of the database.
[0013] The invention may offer one or more advantages. For example,
the techniques described herein may improve the accuracy and
predictability of enterprise planning by enabling organizations to
reconcile corporate models and organizational targets with detailed
forecasts in real-time. The techniques may provide a platform that
delivers collaborative, real-time planning capabilities, without
requiring offline consolidation and aggregation of forecasts.
Because the enterprise planning system can aggregate contribution
data in real-time, all users can be presented with an accurate,
up-to-date view of the numbers. The system provides rapid response
regardless of the number of enterprise users involved in the
planning, thus providing precise planning information.
[0014] Further, the architecture described herein can readily scale
to thousands of users, and may be designed around best planning
practices. In this manner, the system may used to centrally manage
all planning information across operating units and systems within
the enterprise, thus creating a "planning hub." Consequently, users
can work from a single pool of planning data, and can be assured of
the integrity of the data.
[0015] In addition, the techniques promote high user-participation
across the enterprise, allowing planning cycles to be reduced,
e.g., from months to weeks, and best practices, like rolling
forecasting, to be quickly enabled.
[0016] The details of one or more embodiments of the invention are
set forth in the accompanying drawings and the description below.
Other features, objects, and advantages of the invention will be
apparent from the description and drawings, and from the
claims.
BRIEF DESCRIPTION OF DRAWINGS
[0017] FIG. 1 is a block diagram illustrating an environment in
which an enterprise planning system enables and automates the
reconciliation of top-down targets with detailed bottom-up
forecasts.
[0018] FIG. 2 is a block diagram illustrating one example
embodiment of the enterprise planning system.
[0019] FIG. 3 is a block diagram illustrating one embodiment of a
remote computing device for interacting with the system.
[0020] FIG. 4 is a block diagram illustrating an example embodiment
of database servers in which enterprise data is organized to
include a transactional data area and a relational data area.
[0021] FIGS. 5 and 6 are block diagrams illustrating an example
organization of the transactional data area in accordance with a
hierarchy defined by an enterprise planning model.
[0022] FIG. 7 is a flowchart illustrating in further detail the
operation of an enterprise planning system.
[0023] FIG. 8 is a flowchart illustrating in further detail the
real-time aggregation process performed by the enterprise planning
system.
[0024] FIG. 9 is a flowchart illustrating in further detail example
operation of a set of application servers in publishing data from
the transactional data area to the relational data area.
[0025] FIG. 10 is a flowchart illustrating an example mode of
operation of an administration console in controlling the
deployment of multiple enterprise planning models across a set of
application servers.
[0026] FIGS. 11-21 illustrate a number of views presented by a web
browser during an exemplary enterprise planning session.
DETAILED DESCRIPTION
[0027] FIG. 1 is a block diagram illustrating an environment 2 in
which enterprise planning system 3 enables and automates the
reconciliation of top-down targets with detailed bottom-up
forecasts for enterprise 4. Generally, enterprise planning system 3
provides three stages of enterprise planning: (1) a modeling stage,
(2) a contribution stage, and (3) a reconciliation stage. In the
modeling stage, analysts 8, such as the chief financial officer,
senior financial analysts or product and sales analysts, define
requirements and build planning models for the enterprise 4. More
specifically, analysts 8 develop a model having a number of
hierarchically arranged nodes representing various cost centers
within enterprise 4, such as business units or departments.
[0028] During the modeling stage, analysts 8 also establish
corporate targets for each node of the organizational hierarchy.
Analysts 8 then assign one or more enterprise users to each node,
such as managers, supervisors, sales representatives, lab managers,
or the like, that are responsible for enterprise planning for the
corresponding cost center. Each enterprise user may be designated
as a contributor 8 that provides planning data to enterprise system
3, a reviewer that accepts or rejects contributions from
contributors 8, or both. Contributors 8 and reviewers 9 may be
authorized users within enterprise 4, or within other entities
coupled to network 9, such as suppliers 14 and customers 16.
[0029] Finally, analysts 8 define a number of templates for
collecting spending forecast data from the contributors. Analysts 8
include the corporate target data in the templates to facilitate
reconciliation with the forecast data.
[0030] Next, enterprise planning system 3 enters the contribution
phase during which contributors 6 interact with enterprise planning
system 3 and input detailed forecasts in the form of contribution
data. For example, contributors 6 may provide detailed financial
forecasts, revenue forecasts, order forecasts, inventory forecasts,
estimated resource requirements, and the like, depending on the
particular enterprise planning activity being carried out by
enterprise 4.
[0031] During the reconciliation phase, enterprise planning system
3 automates the reconciliation of the forecast data with the
corporate targets provided by analysts 8. In particular, enterprise
planning system 3 operates in accordance with the defined model to
provide a hierarchical planning process having multiple
reconciliation levels. As each of contributors 6 provides his or
her contribution data, enterprise planning system 3 automatically
aggregates the contribution data across enterprise 4 in real-time,
and provides access to the aggregated data to reviewers 9
associated with higher levels of enterprise 4. In particular, upon
receiving contribution data from contributors 6, enterprise
planning system 3 identifies all higher levels of the
organizational model affected by the newly received contribution
data, and calculates new aggregate totals at each level in
real-time.
[0032] Consequently, reviewers 9 view aggregated data across
enterprise 4 in real-time during the enterprise planning session.
At each level, enterprise planning system 3 ensures that reviewers
9, as defined by the nodes of the enterprise model, reconcile the
target data with the forecast data. Each reviewer 9 may, for
example, reject or accept the contribution data in view of
corporate targets provided by analysts 8. This process continues
until the contribution data is ultimately approved by the highest
level of the organizational hierarchy, thereby ensuring that the
contribution data from contributors 6 reconciles with corporate
targets provided by analysts 8.
[0033] In this manner, enterprise planning system 3 may provide
more accurate enterprise planning than with conventional
techniques. For example, enterprise planning system 3 may improve
the accuracy and predictability of enterprise planning by enabling
organizations to reconcile corporate models and organizational
targets with detailed forecasts. The techniques may provide a
platform that delivers collaborative, real-time planning
capabilities, without requiring offline consolidation and
aggregation of forecasts. Because the enterprise planning system
can aggregate contribution data in real-time, all users can be
presented with an accurate, up-to-date view of the numbers.
Further, the architecture of enterprise planning system 3 can
readily scale to thousands of users, and may be designed around
best planning practices. In addition, the techniques enabling high
participation by enterprise users, i.e., contributors 6 and
reviewers 9, allowing accurate planning cycles to be reduced
[0034] Enterprise users may use a variety of computing devices to
interact with enterprise planning system 3 via network 9. For
example, an enterprise user may interact with enterprise planning
system 3 using a laptop computer, desktop computer, or the like,
running a web browser, such as Internet Explorer.TM. from Microsoft
Corporation of Redmond, Wash. Alternatively, an enterprise user may
use a personal digital assistant (PDA), such as a Palm.TM.
organizer from Palm Inc. of Santa Clara, Calif., a web-enabled
cellular phone, or similar device. Network 9 represents any
communication network, such as a packet-based digital network like
the Internet. In this manner, system 2 can readily scale to suit
large enterprises. The enterprise users may directly access
enterprise planning system 3 via a local area network, or may
remotely access enterprise planning system 3 via a virtual private
network, remote dial-up, or similar remote access communication
mechanism.
[0035] FIG. 2 is a block diagram illustrating one example
embodiment of enterprise planning system 3. In the illustrated
embodiment, enterprise planning system 3 includes web servers 20,
application servers 26, and database servers 40.
[0036] Web servers 20 provide an interface for communicating with
enterprise user 18 via network 9. Web servers 20 execute web server
software, such as Internet Information Server.TM. from Microsoft
Corporation, of Redmond, Wash. As such, web servers 20 provide an
environment for interacting with contributors 6, analysts 8, and
reviewers 9 according to software modules 21, which include
analysis module 30, contribution module 32, administration (ADMIN)
console 36, and extension manager 38.
[0037] Software modules 21 may comprise Lotus scripts, Java
scripts, Java Applets, Active Server Pages, web pages written in
hypertext markup language (HTML) or dynamic HTML, Active X objects,
and other suitable modules. Web servers 20 serve up web pages
defined by software modules 21, and communicate the web pages to
computing devices of enterprise users 18. The web pages may include
static media, such as text and graphic imagery, as well as
conventional input media such as text entry boxes, radio buttons,
drop-down menus, and the like, for receiving information from
enterprise users 18.
[0038] Software modules 21 interact with database servers 40 to
access enterprise data 42 including user data 42A, model data 42B,
job data 42C, and configuration data 42D. Enterprise data may be
stored in a number of different forms including one or more data
storage file, or one or more database management systems (DBMS)
executing on one or more database servers. The database management
systems may be a relational (RDBMS), hierarchical (HDBMS),
multidimensional (MDBMS), object oriented (ODBMS or OODBMS) or
object relational (ORDBMS) database management system. Furthermore,
although illustrated separately, enterprise data 42 could be
combined into a single database or other data storage structure.
Enterprise data 42 could, for example, be implemented as a single
relational database, such as SQL Server from Microsoft
Corporation.
[0039] User data 42A stores information for each of users 18,
including the name, email address, and other contact information
for the user. Model data 42B stores the enterprise planning models
defined by the analysts 8. For example, model database 42B stores
information that defines the reconciliation process developed by
analysts 8, including the number of reconciliation levels, the
various "nodes" in the hierarchy, and the contributor 6 associated
with each node. In addition, model data 42B stores the respective
data entry templates of the models for capturing contribution and
review data from users 18. Job data 42C defines administration jobs
for execution application servers 26, and configuration (CONFIG)
data 42D stores basic configuration data for enterprise planning
system 3.
[0040] Application servers 36 provide an operating environment for
execution of business logic modules 46, enterprise planning
extensions 47, and application programming interface (API) 48. In
addition, application servers 36 carry out administration tasks as
defined by job data 42C. In other words, job data 42 provides a
mechanism for queuing job descriptions for pending administrative
jobs for execution by application servers 26.
[0041] Referring to software applications 21, analysis module 30
includes one or more software modules for creating enterprise
planning models, such as financial models for enterprise 4, to
control the entire planning process. For example, analysis module
30 allows analysts 8 to define the various cost centers, the
corresponding owners and the number of reconciliation stages in the
enterprise planning process. In one configuration, analysis module
30 read cost-center structures and ownership from an enterprise
resource planning (ERP) database (not shown). In addition, analysis
module 30 allows analysts 8 to define the "templates" for
collecting contribution data. A template may comprise one or more
multi-dimensional structures that provide an interface for entering
and calculating contribution data. For example, the template may
define cost centers as a dimension within a data cube for selecting
data, with a chart of accounts along the rows, and periods in the
columns. Analysis module 30 stores the enterprise planning models,
as well as the corresponding templates, within model data 42B.
[0042] Analysis module 30 also allows the organization to define a
number of mechanisms for automating the budgeting process and
ensuring that the contributors 6 submit their respective
contribution data timely, and that templates quickly move through
the defined reconciliation stages. For example, using analysis
module 30, the analysts 8 can define timers for triggering
electronic mail messages (emails) to remind the contributors 6 to
access enterprise planning system 3 and complete a particular
template.
[0043] Contribution module 32 include software modules for
presenting the templates to enterprise users 18 designated as
contributors 6, and for capturing contribution data from the
contributors 5. Contribution module 32 captures and aggregates the
contribution data across enterprise 4 in real-time, and provides
access to the aggregated data to reviewers 9 associated with higher
levels of enterprise 4.
[0044] Report generator 34 includes analytical software modules
that generate enterprise planning reports based on the contribution
data received from contributors 6 and stored within model data 42B.
In particular, the analytical software modules allow users 18, such
as analysts 8 and reviewers 9, to formulate complex queries for
generating reports and performing other data analysis functions on
the current data of the enterprise model. These software modules
may be web-based modules having a browser interface, or may be
stand-alone executable programs.
[0045] Business logic modules 46 execute within the operating
environment provided by application severs 26, and provide
functionality for accessing and processing the data stored within
databases 42 in response to software modules 21. In particular,
business logic modules 46 comprise software routines for
implementing the enterprise planning functions, and are invoked by
software modules 21.
[0046] Administration console 36 presents an interface for
controlling the clustering of web servers 20, application servers
26, and database servers 40. Administration console 36 allows the
system administrator to control the number of servers used within
each cluster. The system administrator may, for example, select one
or more servers available within network 9, and direct
administration console 36 to utilize the servers as, for example,
application servers 36. In this manner, enterprise planning system
3 may easily scale to support large enterprises having thousands of
users 18.
[0047] When administrating a task associated with an enterprise
planning activity, administration console 36 may break the task
into a number of jobs, each job associated with a different slice
of the model in accordance with the multi-level, organizational
hierarchy defined by the particular model. For example,
administration console 36 may separate a particular task into a set
of N jobs, where N equals the number of nodes defined within the
hierarchy. Administration console 36 may then distribute the jobs
across the set of application servers 26 for which the model is
deployed.
[0048] Administration console 36 provides a job interface for
viewing jobs queued for processing by application servers 26, and
viewing the load balancing across the clustered application servers
26. Administration console 36 generates job data 42C to define task
for application servers 26. As jobs are queued within job data 42C,
application servers 26 read job data 42C from the database servers
40, and process the jobs to completion. For example, one type of
job involves the "cut-down" process by which the enterprise model
defined within enterprise data 42B is "sliced" for each user.
During this process, application servers 26 identify areas of the
defined models to which users 18 are assigned, either as
contributors or reviewers. Enterprise planning system 3 presents
the respective slices to each user 18 to capture contribution data,
and to reconcile the contribution data with organizational targets.
In this fashion, enterprise planning system 3 need not communicate
the entire model to each of users 18, thereby reducing
communication time as well as resource requirements. Instead, each
user 18 receives only relevant information.
[0049] In addition, administration console 36 allows a system
administrator to control the deployment of enterprise planning
models across application servers 26. In particular, analysts 8 may
define a plurality of planning models for enterprise 4. For
example, analysts 8 may define separate models for revenue
forecasting, inventory management, resource planning, managing
accounts payable, and the like. Administration console 36 allows
the system administrator to create a deployment map that assigns
each model to a set of application servers 26. In other words,
different enterprise models can be deployed on separate application
servers 26, or may share one or more application servers.
[0050] Consequently, the system administrator may finely control
the allocation of computing resources to enterprise planning, and
may adjust the resources to meet the current needs of the
enterprise. The system administrator may adjust the deployment map
to shift the deployment of the models across application servers 26
based on approaching deadlines for the enterprise planning
activities. Specifically, the system administrator may allocate
more computing resources to enterprise models having the earliest
deadlines in view of the likely increased activity by users 18 as
the deadlines approach. As another example, the system
administrator may adjust the deployment map based on current usage
levels for users 18 participating in the enterprise planning
models.
[0051] Administration console 36 allows analysts 8 to modify an
enterprise planning model. For example, analysts 8 may wish to
capture additional contribution data after initiating an enterprise
planning activity. To ease the adoption of the changes to the
model, administration console 36 supports node level modification
and maintenance of an enterprise planning model. In particular,
administration console allows analysts 8 to check-in and check-out
nodes of the model, i.e., to mark the node or otherwise change the
state of the node from "online" to "offline." Consequently, an
analyst 8 can updated a model "slice" associated with the
particular offline, rather than interrupting the enterprise-wide
planning activity. Other users cannot edit the offline node, i.e.,
no contribution data or review input can be saved to the respective
slot for the node within transactional data area 62.
[0052] However, the enterprise contributors associated with the
non-offline nodes may continue to provide and review contribution
data for the enterprise planning session. This feature allows
modification and maintenance on a per-node basis, and allows the
model to remain operational. Accordingly, analysts 8 can modify the
business logic associated with a particular node without taking the
entire model offline.
[0053] Application servers 26 typically process model changes made
by analysts 8. Specifically, in the event analysts 8 modify an
enterprise model during the planning activity, application servers
26 may be used to reconcile contribution and review data received
from users 18 with the updated model. Alternatively, administration
console 36 may direct application servers 26 to facilitate remote
reconciliation on the computing devices of users 18. Upon
authenticating access by users 18 subsequent to the model change,
authentication servers 44 may "push" reconciliation jobs to the
local computing devices. The remote computing devices reconcile the
contribution data and review data of users 18 with the updated
model, and save the reconciled data to enterprise planning system
4. This may be advantageous in that enterprise planning system 3
need not be taken offline to update enterprise models, and that
computing resources to process the updates can be distributed
across the remote computing devices of users 18.
[0054] Extension manager 38 provides an interface by which a system
administrator can install and selectively deploy extensions 47 to
easily provide additional enterprise planning functions to system
10. In general, three classes of extensions can be added: (1)
administration extensions, (2) server-side extensions, and (3)
client-side extensions. Administration extensions comprise software
modules that execute within, or invoked by, administration console
36. Consequently, administration extensions are typically used to
provide additional administrative functionality, and may generate
administration jobs for execution by application servers 26.
[0055] Server-side extensions typically execute within the
operating environment provided by application servers. These
extensions may be used to facilitate workflow integration, custom
initialization, or custom publishing of aggregated contribution
data during the planning activity.
[0056] In contrast, client-side extensions comprise software
modules that execute within the operating environment of the remote
computing devices of users 18, typically within a web browser
environment. Contribution module 32 automatically searches
extensions 47 for newly installed extensions, and downloads the
extensions to users 18 upon their next access. In particular,
contribution module 32 may load and invoke the extension on the
remote computing device immediately upon user access, or upon
demand. Although client-side extensions typically operate within
the operating environment of the remote computing devices, the
extensions may interact with server-side components.
[0057] To facilitate the incorporation of extensions, enterprise
planning system 3 provides an application programming interface
(API) 48 by which extensions 47 can directly access and manipulate
models within model data 42B, as well as other components of
enterprise planning system 3. Via extension manager 38, the system
administrator can register new extensions 48 with system 10, and
define inputs for launching the extensions, e.g., buttons or other
graphical icons.
[0058] Extension manager 38 allows the system administrator to
selectively deploy extensions based on the role assigned to the
particular user 18. In particular, extension manager 38 allows the
system administrator to assign extensions to all contributors 6,
and to all reviewers 9. In addition, extension manager 38 allows
the system administrator to assign extensions to different slices
of enterprise planning models stored within model data 42B. In this
manner, extensions may be assigned to different cost centers,
different business departments, and the like. Furthermore,
extensions may be assigned based on the level of a reviewer 9
within the hierarchy defined by the particular model. For example,
reviewers 9 of a certain level of the hierarchy, e.g., controllers
for cost centers, may be required to complete a best-practices
extension that provides detailed best practices validation on all
aggregated contribution data. Extension manager 38 may store
user-specific extension information within user data 42A indicating
which extensions are assigned to each of users 18, and possibly
setting user-specific properties for the extension. This
flexibility advantageously allows an enterprise planning model to
be adapted and customized as the enterprise planning session
extends deeper into enterprise 10.
[0059] One example of an extension is an extension that provides a
wrapper around an off-the-shelf collaborative network-based
planning tool, such as NetMeeting from Microsoft Corporation.
Instead of rejecting contribution data, a reviewer 9 can invoke the
extension to conference in the subordinate, and directly access
model data 42B to review the contribution data together. Another
example is an extension that enables real-time validation of a
contribution against other sources. Other examples of extensions
include: (1) extensions for customized reporting functions required
by certain users 18 within the hierarchy, (2) extensions for
exporting planning data to other applications, e.g., a spreadsheet
application, (3) extensions for driving newly developed printing
engines, (4) extensions for importing enterprise data, and (5)
extensions for interfacing with a document management system.
[0060] Extension manager 38 allows the system administrator to map
extensions 47 to events or messages within system 3. For example,
the system administrator may install a new extension, and require
that the extension be invoked upon receiving contribution data from
one of contributors 6 via contribution module 32. This feature may
be particularly useful for deploying best practices validation of
contribution data or enforcement of other enterprise requirements.
As another example, an extension may be used to enforce
reconciliation of top-down corporate targets with bottom-up
forecasts within a predefined defined percentage, e.g., ten
percent. As another example, an extension may be used to reduce
forecasts to a certain level or by a particular percentage.
Accordingly, uniform decreases in forecasts can easily be required
and enforced across enterprise 4.
[0061] In one embodiment, extensions 47 may comprise software
modules that conform to the component object model (COM).
Consequently, an ActiveX client may be easily used to invoke
extensions 47. Each extension 47 may provide one or more common
interfaces for invocation and control, e.g., by contributor module
32 or administration console 36.
[0062] FIG. 3 is a block diagram illustrating one embodiment of a
computing device 50, including various software modules executing
thereon, when operated by a user 18, such as a contributor 6 or a
reviewer 9. In the exemplary embodiment, computing device 50
includes web browser 52, calculation engine 54, template 56 and
data cube 58. When a user 18 directs computing device 50 to access
enterprise planning system 3, calculation engine 54, and template
56 are downloaded and installed within web browser 52.
[0063] In one embodiment, calculation engine 54 comprises a forward
calculation engine 54 wrapped in an Active X object built in an
array-based language. Template 56 comprises an Active X control
that includes any necessary drivers for entering and manipulating
budget forecast data. Template 56 includes a stand-alone data cube
58 containing the top-down target data, and the bottom-up
contribution data, and allows all calculations to be performed
locally. Therefore, after the download is complete, each
contributor 6 can modify his or her respective contribution data
within template 56, and perform calculations without accessing
enterprise planning system 3. As ActiveX components, calculation
engine 54, template 56 and data cube 58 are maintained locally via
computing device 50. As such, the contributor 6 will only
experience network delays when template 56 and calculation engine
54 are initially downloaded, as well as when template 56 is saved
at the end of a session.
[0064] To interact with enterprise planning system 3, each of
contributors 6 uses browser 52 to interact with template 56 to
provide respective contribution data, e.g., by completing cells of
a displayed grid, and viewing the dynamic changes that occur to
calculated items within the grid. Because calculation engine 54 is
resident within web browser 52, the cell entries do not have to be
resubmitted to enterprise planning system 3, recalculated, and then
re-posted to the web browser 52 via network 9. If the contributor 6
wishes to end the planning session, but has not finished the
process, the contributor 6 can save template 56 and data cube 58 to
enterprise planning system 3. When the contributor 6 wishes to
continue the planning session, he or she can access enterprise
planning system 3, at which time the appropriate template 56 and
data cube 58 will be loaded in web browser 52 for further editing.
When the contributor 6 is satisfied with the budget data entered
within template 56, the contributor 6 can submit the data to
enterprise planning system 3. As each contributor 6 provides his or
her contribution data, or accepts the contribution data, enterprise
planning system 3 automatically aggregates the contribution data
across enterprise 4 in real-time, and provides access to the
aggregated data to reviewers 9 associated with higher levels of
enterprise 4.
[0065] In similar fashion, each of reviewers 9 interacts with
enterprise systems 3 via web browser 52 executing upon his or her
remote computing device 50. Each reviewer 9 may reject or accept
the contribution data in view of corporate targets provided by the
analysts 8. This process continues until the contribution data is
ultimately approved by the reviewers associated with the highest
level of the organizational hierarchy, thereby ensuring that the
contribution data from the contributors reconciles with corporate
targets.
[0066] In one embodiment, web browser 52 includes inline
compression module 53 for automatically compressing communication
to enterprise planning system 4, and decompressing communications
received from the system. In particular, inline compression module
53 automatically intercepts outgoing buffers transmitted from web
browser 52 to system 10 via the hypertext transport protocol
(HTTP), and automatically compresses the buffers prior to
transmission. Similarly, inline compression module 53 intercepts
incoming HTTP buffers, and determines whether the buffers are
compressed. If the buffers are compressed, inline compression
module 53 automatically decompresses the buffers, and forward the
decompressed buffers to web browser 53. In this manner, inline
compression module 53 seamlessly compresses and decompresses
communications between computing device 50 and enterprise planning
system 3, leading to possible efficiency gains within system 2.
[0067] In one embodiment, enterprise planning system 3 makes use of
a single active server page (ASP) to receive the compressed HTTP
buffers, and direct the compressed buffers to appropriate business
logic modules 46 for decompression and processing. A header with
each HTTP buffer may include a byte count or other information
indicating whether the buffer is compressed, and an identifier for
an appropriate business logic module 46.
[0068] FIG. 4 is a block diagram illustrating an example embodiment
of database servers 40 in which enterprise data 42 is organized to
include a transactional data area 62 and a relational data area 63.
In general, transactional data area 62 supports real-time data
acquisition and aggregation from users 18, while relational data
area 63 is used for report generation and complex data
analysis.
[0069] More specifically, database servers 40 store contribution
data received from contributors 6 in transactional data area 62,
and publish the contribution data from transactional data area 62
to relational data area 63, e.g., on a periodic basis.
Transactional data area 62 includes a number of slots 66 that are
hierarchically related in accordance with the enterprise model.
Transactional data area 62 includes a set of contribution slots 66
to store contribution data received from contributors 6, and a set
of aggregations slots 67 to store aggregated data calculated from
the contribution data in real-time and in accordance with the
hierarchy defined by the model. Consequently, transactional data
area 62 includes a transaction slot 67 for each of the enterprise
contributors 6 to store the contribution data received from the
respective enterprise contributor. In addition, transaction data
area 62A associates each reviewer 9 with at least one of the
aggregation slot 67 for each reviewer 9. For example, an enterprise
model may have N hierarchically arranged nodes, each node defining
at network user and designating the user as one of a contributor
and a reviewer. In this configuration, transactional data area
comprises N slots, including an aggregation slot for each reviewer
and a transaction slot for each contributor defined by the
model.
[0070] FIGS. 5 and 6 are block diagrams further illustrating the
organization of transactional data area 66 in accordance with a
hierarchy defined by an enterprise planning model. FIG. 5 depicts
an example hierarchy defined by an enterprise planning model for an
example fictitious pizza chain: Pizza Palace, Inc. Hierarchy 70 is
horizontally organized around the various geographic regions
occupied by the franchise, regions 1 through 5, and vertically
organized into three reconciliation levels. Enterprise goals and
targets are set by the analysts 8, and are distributed down through
the various nodes of the hierarchy. The individual stores of the
franchise, referred to as outlets, occupy the bottom level, i.e.,
Level III, and provide contribution data.
[0071] Each node of Level 1 has a corresponding contributor 6 that
is responsible for entering contribution data. Similarly, each node
of Levels I, II is associated with a reviewer 9 for reconciling the
contribution data in view of the corporate targets defined by
analysts 8. For simplicity, FIG. 5 illustrates one of the
contributors, Andy associated with Outlet A, and two reviews: Peter
associated with Region 1, and Guy associated with the node. In this
example, Guy is the Chief Financial Officer for Pizza Palace, Inc.
and is responsible for the overseeing all regions. Guy, therefore,
is listed as an "owner" of root node 29 and as a "reviewer" for all
Regions 1-5. Peter is a middle level manager charged with
overseeing Region 1. As such, Peter is listed as the owner of
Region 1 and reviewer for Outlet A. Andy, a manager of a local
pizza store, is listed as the owner for Outlet A.
[0072] Each node of hierarchy 70 is associated with one or more
corresponding templates within model data 42B, depending upon the
node's level within the hierarchy. For example, each outlet within
Level III is associated with a single template for capturing
forecast information. At Level II, each region is associated with
the templates of its corresponding child nodes, i.e., the outlets
within the region. Root node 72 of hierarchy 70 is, therefore,
associated with all of the templates for the company.
[0073] FIG. 6 illustrates an example organization of transactional
data area 62 for supporting real-time aggregation of contribution
data in accordance with hierarchy 70 defined by the enterprise
planning model for Pizza Palace. In this example, transactional
data area 62 includes contribution slots 66 for each node of Level
III, i.e., each of Outlets A-H. Each contribution slot 66 stores
contribution data for the contributor 6 associated with the
respective node of Level III of hierarchy 70.
[0074] Similarly, transactional data area 62 includes aggregations
slots 67 for each node of Levels I, II, i.e., root node 72 and the
nodes corresponding to Regions 1-5. Each aggregation slot 67 stores
aggregated contribution data for its child nodes, as defined by
hierarchy 70 and represented in FIG. 6 by arrows. For example,
aggregation slot 74 corresponds to root node 72, and stores
aggregated data calculated by totaling all data received from
Regions 1-5. As another example, aggregation slot 76, corresponding
to Region 2, stores aggregated data calculated from contribution
data for Outlets B-D. In this manner, transactional data area 62
provides an accurate, up-to-date view of data for all levels of the
model, thus facilitating enterprise-wide planning.
[0075] FIG. 7 is a flowchart illustrating in further detail the
operation of enterprise planning system 3. Initially, analysts 8
interact with enterprise planning system 3 to develop a planning
model that include one or more data cubes having multiple
dimensions (80). For example, for Pizza Palace, Inc., the model may
define a single data cube having thee dimensions: (1) a first
dimension listing specialty pizzas, e.g., meat lovers, vegetarian,
barbeque, seafood, ham and mushroom, (2) a second dimension for
weekly sales forecasts, and (3) a third dimension for corporate
targets.
[0076] Analysts 8 also define an organizational hierarchy for
controlling the enterprise-wide planning process (82). For Pizza
Palace, for example, analysts 8 may define an organization
hierarchy having fourteen nodes as illustrated in FIG. 5. Analysts
8 assign one or more enterprise users to each node, and designate
each user as a contributor, reviewer, or both. In addition,
analysts 8 may designate one of the users associated with each node
as an owner of that respective node.
[0077] Upon receiving the organizational hierarchy, application
servers 26 of enterprise planning system 3 processes the model in
view of the hierarchy to "slice" the model for each defined user.
In other words, application servers 26 apply the hierarchy to the
model as if the hierarchy were an additional dimension, and
identifies a respective portion of the model for which each user
can access. Application servers 26 associate each node in the
hierarchy with a slice across the other dimensions of the model. By
slicing the model in this manner, enterprise planning system 3 need
not communicate the entire model to the remote computing device of
the user, but need only communicate the relevant portion of the one
or more data cubes of the model.
[0078] In addition, application servers initialize enterprise data
42, including creating the appropriate number of aggregation slots
66 and contribution slots 67 of transactional data area 62, as well
as creating create the tables and relationships of relational data
areas 63.
[0079] Next, analysts 8 interact with the enterprise planning
system 3 to provide target data for the enterprise (86), and
contributors 6 interact with the system to provide detailed
forecasts in the form of contribution data (88). Upon receiving the
contribution data, application servers 26 update contribution slots
67 of transaction data areas 66 to store the contribution data, and
update aggregation slots 66 in real-time to store aggregate totals
for each of the upper levels nodes of the enterprise hierarchy.
[0080] In this manner, the aggregate totals are readily available
for reviewers 9 across enterprise 4. Consequently, reviewers 9 can
access enterprise planning system 3, and immediately provide review
input either rejecting or accepting the contribution data and the
aggregate totals in view of the target data provided by analysts 8
(92). During this process, application servers 26 periodically
publish contribution data and aggregate data from transactional
data area 62 to relational data area 6 (94) for creation of
analytical reports and other statistical analysis by report
generator 34 (96). Enterprise planning system 3 repeats the
reconciliation process until the contribution data and aggregate
totals are accepted by the high-level reviewer of the
organizational hierarchy (98).
[0081] FIG. 8 is a flowchart illustrating in further detail the
real-time aggregation process of enterprise planning system 3. Upon
receiving an access request from one of contributors 6 (99),
application servers 26 access enterprise data 42 and identify a
respective contribution slot for the contributor (100). Application
servers 26 retrieve from the identified slot any contribution data
previously stored by the contributor, and communicates an input
template 56 and contribution engine 54 to the contributor 6
(102).
[0082] Upon receiving new or updated contribution data from the
contributor 6 (104), application servers 26 update the respective
contribution slot to store the contribution data (106). Next,
application servers 26 selectively update the aggregate totals of
aggregation slots 66 for any parent aggregation slots related to
the updated contribution slot. In particular, application servers
26 identifies the immediate parent aggregation slot for the updated
contribution slot based on the defined hierarchical model (108),
calculates new aggregate totals for the parent slot based on the
updated contribution slot (110), and stores the new aggregate
totals to the parent slot (112). Application servers 26 repeat this
process until all related higher-level aggregation slots have been
updated (114).
[0083] In one embodiment, application servers 26 organize
transactional data area 62 as a single table having a set of rows.
Each row corresponds to a respective node in the defined
organizational hierarchy. Application servers 26 store respective
contribution data or aggregation data within each row, and may
store the data as a row that contains a single "blob" of data.
Specifically, application servers 26 may write the data for a given
row as a single string or text or binary data. In one embodiment,
each row is stored as packed text that conforms to the extensible
markup language (XML). The packed XML describes each cell for the
slice of the model that pertains to the user associated with the
row, as well as the current value for the cells. When initializing
transactional data area 62, application servers 26 extract metadata
from the one or more data cubes of the model, and create an XML
representation of each "slice" of the model within the respective
slot.
[0084] When updating the contribution data, the XML may be
generated by the remote computing device of the user. The remote
computing device may generate the XML, and communicates the XML as
part of the HTTP buffer, either in compressed or uncompressed form.
Alternatively, application servers 26 may generate the XML.
[0085] To update the aggregate totals in real-time, application
servers 26 parse the XML for the respective parent aggregation
slots to quickly retrieve current values for the cells, and replace
the packed XML with a new entry having updated aggregate totals.
The aggregate data may be stored in XML form as a linear array
having a set of cells to store the aggregate totals. Consequently,
application servers 26 may retrieve the linear array from one
aggregation slot, overlay the array with the array of a parent
aggregation slot, and quickly recompute the aggregate totals for
the parent slot.
[0086] FIG. 9 is a flowchart illustrating in further detail example
operation of application servers 26 in publishing data from
transactional data area 62 to relational data area 63. Application
servers 26 may publish the data periodically, e.g., every 15
minutes, 30 minutes, and the like. Alternatively, or in addition,
application servers 26 may publish the data in response to an
event, e.g., submission of contribution data from a contributor 6,
or review input from a reviewer 9.
[0087] To publish the data, application servers 26 pass the
contribution data of each contribution slot 67 to identify a set of
date elements and respective values (116). As described above, each
slot 67 may contain packed XML describing a slice of the enterprise
planning model. Application servers 26 decompress the packed XML,
and identify the contained cells of the data cubes of the model, as
well as the current values for the cells.
[0088] Next, based on the model, application servers 26 select one
or more tables from relational data area 63 that correspond to the
parsed contribution data (118). For example, application servers 26
may identify a Sales table to store forecasted product sales.
[0089] Finally, application servers 26 write the parsed data into
the identified tables of relational data area 63. Consequently,
reporting module 34 may issue complex queries to database servers
40 to generate sophisticated reports or perform similar analysis on
contribution data captured across enterprise 4.
[0090] FIG. 10 is a flowchart illustrating an example mode of
operation of administration console 36 in controlling the
deployment of multiple enterprise planning models across
application servers 26. Initially, administration console receives
input identifying one or more application servers 26 (122). For
example, a system administrator may select the application servers
26 from a list of servers available within a local area network.
Alternatively, the system administrator may specify a particular
name, Internet Protocol (IP) address, or similar communication
handle for communicating with the application server.
[0091] In response, administration console 36 queries the
identified applications servers for a description of the computing
resources present on each server, such as the number of processors
present within each application servers 26 (124). Administration
console 36 may present this information to the system administrator
for use in deploying the various planning models of enterprise
4.
[0092] Next, administration console 36 receives input from the
system administrator that assigns each model to a set of
application servers 26 (126). Based on the input, administration
console 36 generates a deployment map associating each model with
respective sets of the application servers, and stores the map
within enterprise data 21 (128).
[0093] Based on the mapping, business logic modules 46 generates
jobs for administering the enterprise planning sessions, and stores
job descriptions within job data 42C. Application servers 26 read
and process the job descriptions, as described above, in accordance
with the deployment map (130). In this manner, different enterprise
models can be deployed on separate application servers 26, or may
share one or more application servers.
[0094] The deployment map may be adjusted, either in response to
input from the system administrator or dynamically based on current
loading levels of application servers 26 (126). Specifically,
administration console direct regeneration of the deployment map,
thereby rebalancing the deployment of the enterprise planning
models across clusters of application servers 26.
[0095] FIGS. 11-19 illustrate a number of views of web browser 52
during an exemplary enterprise planning session for the fictitious
Pizza Palace Inc. described above. For example, FIG. 11 illustrates
one embodiment of a window 160 displayed by web browser 52 when
Guy, the CFO, accesses enterprise planning system 3 in order to
check on the progress of the various budgets for the pizza
franchise. In this example, Guy has accessed enterprise planning
system 3 using Internet Explorer from Microsoft Corporation running
Shock Wave.TM. from Macromedia.TM. Inc.
[0096] Window 160 displays: 1) a customizable headline 162 to all
contributors and reviewers of a give budget template, 2) a link 164
for displaying instructions, 3) the name of the contributor, and 4)
the current date. Enterprise planning system 3 may use the
authentication built into the operating system of the remote
computing device for security such that new passwords do not have
to be created and managed separately.
[0097] Window 160 includes a left frame 165 that displays the
hierarchal model 138 defined by analysts 8 for the pizza chain. The
hierarchy, as described above, includes five sales regions, with
Region 2 having 3 pizza stores (Outlet B-Outlet D). The hierarchy
represents the workflow of the corporation and, therefore, may be
intuitive to the contributors. Furthermore, each contributor has a
limited view such that left frame 165 only displays the portion of
the hierarchal model 138 for which the particular contributor has
access. Because Guy is a high-level executive defined as a reviewer
for all five regions, he can view the entire hierarchy.
[0098] Right frame 166 and left frame 165 cooperate in that when a
user selects a node in the hierarchy within left frame 165, right
frame displays the details of the selected node and its children.
More specifically, right frame 166 displays tables detailing the
selected node and each of its children. Each table shows: a) a node
name, b) an operating state for the node, c) a time of last
modification to the template, d) whether the budget template has
been opened by the owner of the node, e) a name of the
owner/reviewer, f) whether the budget template has been reviewed,
and g) actions that the user may take on the node.
[0099] At the bottom level in the hierarchy, each node has three
workflow states: a) NS--the budget has not been started, b)
WIP--the budget is a "work in progress" such that the owner has
input some data but has not finished, and c) LOCKED--the owner has
submitted the budget for review. Once the budget is submitted, the
owner cannot make changes unless the next level reviewer rejects
the submission, which changes the state of the lower line node back
to WIP.
[0100] The view for Andy, a manager for a local pizza store, is
quite different than from Guy. FIG. 12 illustrates an example
window 170 displayed by web browser 52 when Andy accesses
enterprise planning system 3. As illustrated by FIG. 12, Andy can
only view Outlet A, i.e., the outlet for which he is responsible.
Because Andy has not started the budgeting process, table 172 of
the right frame displays the NS state for the node.
[0101] FIG. 13 illustrates a window 180 displayed when Andy clicks
on Outlet A and initiates the enterprise planning process. At this
point, web browser 52 downloads template 56 and data cube 58. This
is one of the few times when there is traffic across network 9. As
the calculation engine 54 resides on the client, no web traffic
takes place as the user enters budgeting information. Andy
interacts with window 180 to input spending forecast data 182, but
cannot update target data 184 that has been set by analysts 8, and
cannot overwrite formulas embedded within template. In this manner,
window 180 allows Andy to view the financial targets set by
analysts 8 while entering the detailed forecasting information.
Calculation engine 54 allows window 180 to operate as an
intelligent spreadsheet that supports, arithmetic operations,
conditional logic, weighted and time averages and a number of other
operations. In addition, the analysts can configure window 180 to
provide context sensitive help for the row, column and page items.
Upon entering spending forecast data 182, Andy can save the
information and continue the process later or can submit the
forecast information to Peter for review.
[0102] When Andy saves the template, as illustrated in FIG. 14, web
browser 52 displays window 190, which reflect the state of the node
as a "work in progress" (WIP). In this state, Andy can return and
continue to edit the forecast data and submit the forecast data for
review by Peter, as illustrated by window 200 of FIG. 15. Once the
forecast data is submitted, the state of the node is changed to
LOCKED, as indicated by window 210 of FIG. 16. In this state, Andy
cannot modify the forecast information unless Peter reviews the
template and rejects the information.
[0103] FIG. 17 illustrates an example window 220 displayed by web
browser 52 when Peter accesses enterprise planning system 3 in
order to review the budget information for which he is responsible.
As illustrated by FIG. 17, Peter is defined as the owner for Region
1 and the reviewer for Outlet A. Upon logging in, Peter is
immediately able to tell that Andy has submitted the budget
information, which is reflected by the LOCKED state displayed by
table 222 of the right-hand window. In addition, because all of the
child nodes to Region 1, i.e. Outlet A, have submitted forecast
information, table 224 displays the state of Region 1 as READY,
indicating Peter can review all of the budget information.
[0104] FIG. 18 illustrates an example window 230 displaying the
template when selected by Peter for review. Notably, all
information, including the forecast data 232 set by the owner
(Andy) and the target data 234 set by the financial analysts, is
read-only and cannot be modified. As such, Andy has two options as
a reviewer: (1) reject the forecast information and send the grid
back to Peter for modification, or (2) approve the forecast
information such that the template can be reviewed by Guy, the
designated reviewer for Region 1. At this level, the node has five
possible states. The first three are similar to the Level I nodes:
NS (not started), WIP (work in progress) and LOCKED. In addition,
higher-level nodes can also be INCOMPLETE and READY. The INCOMPLETE
state occurs when at least one child node is in the NS state, i.e.,
when a person reporting to the reviewer has not started the
budgeting process.
[0105] Thus, reviewers 9 can quickly tell if the template has not
been viewed, and that the owner needs some added prompting. The
READY state occurs when all child nodes have completed the
budgeting process. At this point, the reviewer is the critical path
of the budgeting process and must either reject or submit the data
from the subordinates. One advantage of this approach over other
methods of data collection is that the middle level managers have a
simple and efficient method of showing upper level management that
they have approved of, and are committed to, the budgeting
forecasts.
[0106] FIG. 19 illustrates an example view of the information when
Peter rejects the information from Outlet A. Outlet A has
transitioned back to the WIP state, which therefore also moves
Region 1 to the WIP state. Andy, the owner, automatically receives
an e-mail from Peter, his reviewer, telling him why the submission
was rejected. This reconciliation process continues until
acceptable budget information is ultimately propagated upward
through all of the levels of the hierarchy.
[0107] FIG. 20 illustrates an example view presented by browser 52
when an analyst 8 creates and maintains an enterprise model,
including assigning owners to the various nodes of the hierarchy.
FIG. 21 illustrates an example view presented by browser 52 when
the analyst defines an access level (e.g. read vs. write) for each
node.
[0108] Various embodiments of the invention have been described.
These and other embodiments are within the scope of the following
claims.
* * * * *